Abstract: A computer implemented method for storing and retrieving data elements in a computer memory comprises configuring, by a processor, the computer memory according to a data structure, the data structure including: a data element array including a plurality of sorted data elements, each data element associated with a position in the data element array; and a cluster element array including one or more cluster elements, each cluster element defined by one of one data element from the data element array or a plurality of continuous data elements from the data element array, wherein each cluster element is associated with a cluster code for determining the position of one or more data elements in the data element array, the cluster code correlating each data element defining the cluster element with the position of the data element in the data element array.

Abstract: Aspects of the disclosure relate to transliteration of machine interpretable languages. A computing platform receive a source query formatted in a first format for execution on a source database. The computing platform may execute the source query on the source database to produce a first data result. The computing platform may input the first data result into a reversal logic engine to produce a target query formatted in a second format corresponding to a target database. The computing platform may execute the target query on the target database to produce a second data result. Based on identifying that the second data result matches the first data result, the computing platform may validate the target query. Based on identifying that the second data result does not match the first data result, the computing platform may adjust the reversal logic engine based on the discrepancy.

Abstract: A database replication system comprises a plurality of replica data nodes and a master data node. The master data node is configured with an acknowledgement requirement that comprises an acknowledgement threshold that is less than a total number of data nodes in a plurality of data nodes. The master data node is configured to send, to the plurality of replica data nodes, a transaction log record that includes an update to data in the master database that has not been committed to the master database, receive acknowledgements of the transaction log records and based on a determination that the received acknowledgements of the transaction log record meet the acknowledgement requirement, set the transaction log record as a master node last acknowledged transaction log record in a master node transaction log. The last acknowledged transaction log record can be used to control recovery.

Abstract: An automatic rule generation and evaluation system enables a user to generate rules and evaluate the rules even as the rules are generated. The user employs a rules workbench user interface (UI) to provide input regarding the rules to be implemented on data obtained from a plurality of data sources. The rules workbench UI generates scripts from the user input. The scripts are employed to build a model and generate queries. Displaying the result sets obtained from executing the queries enables the user to evaluate the rules in real-time. If the user is satisfied, the user may finalize the rules, else the user can further modify the rules and the steps of rule modification and rule evaluation may be iterated until the rules are finalized.

Abstract: Object scriptability includes receiving a high-level language script describing at least one data-analysis object, including a node representing the data-analysis object in a graph-based data structure including a plurality of nodes, where each node from the plurality of nodes represents a respective data-analysis object in a data analysis system, where each node from the plurality of nodes is connected to at least one other node from the plurality of nodes by an edge, and where the edge represents a relationship between the respective objects in the data analysis system.

Abstract: Systems and methods are disclosed herein for modifying suggestion metadata in an electronic document. A copy request is received to copy a portion of the electronic document. The portion of the electronic document includes a suggestion having metadata that indicates the suggestion was made by a first user. The copy request is received from a second user. A paste request to paste the copied portion is received from the second user. Responsive to determining to modify the metadata of the suggestion, the indication that the first suggestion was made by the first user is replaced with an indication that the first suggestion was made by the second user.

Abstract: Various embodiments provide a tracing system or a tracing method that enables an installed software application to be launched with relevant data regarding a user's activity on the client device before installation of the software application. A tracing system of an embodiment may comprise one or more of a server including a database, a web page module configured to be integrated in a website, and an application module configured to be integrated in a software application.

Abstract: The methods and systems for improving communication distribution. In particular, the methods and systems for improving communication distribution in environments where there is both the need for end-user specific data (e.g., customized content) and/or data storage constraints. For example, in order to address the security/privacy concerns during communication distribution, the methods and systems use a novel architecture that limits the amount of data that must be stored. Specifically, the system does not require permanent storage of communications featuring end-user specific data prior to the distribution of these communications. Accordingly, the storage requirements are greatly diminished, and privacy/security concerns are avoided.

Abstract: An information processing device receives material data, relating to a material, that have been sent from a user terminal. The information processing device performs analysis in accordance with one or more analysis techniques with respect to the material data to thereby acquire analysis result data representing analysis results. The information processing device sends the analysis result data to the user terminal.

Abstract: Methods and systems for storing and managing biosystem on a chip data disclosed. To store the data, operation data from the biosystem on a chip may be stored in a database. To manage use of the stored data, a graph representation of the biosystem on a chip. The nodes of the graph representation may correspond to the architectural features of the biosystem on a chip. The edges between the nodes may be based on whether the corresponding architectural features are in communication with one another. Each of the nodes may be associated with pointers that point to portions of the operation data in the database that is relevant to the architecture feature associated with the respective node.

Abstract: Techniques are disclosed relating to index metadata that is usable for accessing multi-level data structures. A computer system may operate a database, including maintaining a set of records having a set of corresponding keys. The computer system may create multi-level data structures that facilitate key range lookups against those records. A given multi-level data structure may store key information indicative of a subset of the corresponding keys. The computer system may create separate index metadata that is usable for accessing the multi-level data structures. The index metadata may specify indications of key information that is stored in the multi-level data structures and locations of the multi-level data structures. The computer system may perform a key range lookup that includes using the index metadata to determine a particular set of the multi-level data structures whose key information corresponds to a key range of the key range lookup.

Abstract: A method, computer system, and a computer program product for searching are provided. The method may include receiving a word and a context of the word. The context may include additional words. A first word embedding may be generated by inputting a sequence into a word embedding model that resultantly outputs the first word embedding. The sequence may include the word and the context that are concatenated to each other in the sequence. The first word embedding may be compared with other word embeddings. The other word embeddings may have been generated by inputting respective text portions of other texts into the word embedding model. A candidate match of the other texts may be presented. A respective word embedding of the candidate match may be, of the other word embeddings, most similar to the first word embedding according to the comparing.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate a dynamic cross-platform ask interface and utilize a cross-platform language processing model to provide platform-specific, contextually based responses to natural language digital text queries. In particular, in one or more embodiments, the disclosed systems utilize machine learning models to extract registered intents from digital text queries to identify platform-specific configurations associated with the registered intents. Utilizing the platform-specific configurations, the disclosed systems can generate tailored platform-specific requests for information, as well as customized end-user search results that cause client devices to efficiently, accurately, and flexibly render platform-specific search results.

Abstract: Implementations include querying metadata of data objects to define a sub-set of data objects, each data object in the sub-set of data objects including a generic text field and/or an attachment field, and, for each data object in the sub-set of data objects, processing historical data of a data object to identify a set of data types, the historical data stored within a field of a table of a database system, providing a recommendation for a first extension corresponding to a first data type, and receiving user input indicating acceptance of the recommendation for the first extension and, in response, automatically providing extension code that is executable to add a field extension to the table and to modify a UI of an application for input of values corresponding to the first data type, and executing the extension code to deploy the extension and to modify the UI.

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for facilitating data visualization generation. In one implementation, dataset intent data, visual design intent data, and insight intent data determined from a user input natural language query are obtained. A set of candidate intent recommendations is generated using various combinations of the dataset intent data, visual design intent data, and insight intent data. Each of the candidate intent recommendations is incorporated into a set of visualization templates to determine eligibility of the candidate intent recommendations. For eligible candidate intent recommendations, a score associated with a corresponding visualization template is determined. Based on the scores, a candidate intent recommendation and corresponding visualizations template is selected to use as a visual recommendation for presenting a data visualization.

Abstract: A method including analyzing the query data to formulate one or more groups of synonym candidates, wherein each synonym in the one or more groups of synonym candidates is categorized in one or more synonym candidate categories. Reformulating the first search query by removing at least one synonym candidate from the first group of synonym candidates to form a first set of synonyms such that each synonym in the first set of synonyms is categorized in the synonym candidate category that matches the search query category of the search query, wherein the at least one synonym candidate removed from the first group of synonym candidates is not categorized in the synonym candidate category.

Abstract: Methods, systems, and devices supporting primitive-based query generation are described. A database system may receive a natural language query associated with a subset of data sets stored at the database system, determine a set of tokens included in the natural language query, and label one or more tokens of the set of tokens with one or more primitives from a set of supported primitives associated with the subset of data sets. The database system may determine a set of higher order concepts corresponding to query operations, query conditions, or both based on the one or more labeled tokens. The database system may train a neural network to learn a grammatical structure of the natural language query and generate a database query for querying the database system based on the one or more labeled tokens, the set of higher order concepts, and the neural network.

Abstract: A question answering (QA) system comprising memory for storing instructions, and a processor configured to execute the instructions to ingest source documents that include structured data and unstructured data to create a knowledge base, wherein the unstructured data includes table data; create table annotations to represent the table data; store the ingested structured data, unstructured data, and the table annotations in the knowledge base; and determine answers to questions using the knowledge base.

Abstract: Systems, apparatus, methods, and articles of manufacture provide for generation, execution, and visualization of data queries (e.g., SQL statements) and their results, based on natural language input from a user. In one example implementation, a dashboard system provides a voting lounge and personalized and crowdsourced dashboards.

Abstract: A computer device receives a request to search a corpus of documents for an entity, wherein the request includes a non-name identifier of the entity. The computing device identifies entries of text within the corpus of documents that reference the non-name identifier. The computing device applies natural language processing (NLP) to content associated with the identified entries within the corpus of documents, wherein the NLP identifies candidate entities associated with the non-name identifier. The computing device selects an entity from the candidate entities based, at least in part, on distances between the candidate entities and references to the non-name identifier in the identified entries. The computing device returns the selected entity to a submitter of the request.